Boosting optimum-path forest clustering through harmony Search and its applications for intrusion detection in computer networks

In this paper we propose a nature-inspired approach that can boost the Optimum-Path Forest (OPF) clustering algorithm by optimizing its parameters in a discrete lattice. The experiments in two public datasets have shown that the proposed algorithm can achieve similar parameters' values compared to the exhaustive search. Although, the proposed technique is faster than the traditional one, being interesting for intrusion detection in large scale traffic networks. © 2012 IEEE.

A nature-inspired approach to speed up optimum-path forest clustering and its application to intrusion detection in computer networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An Optimum-Path Forest framework for intrusion detection in computer networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Intrusion detection in computer networks using optimum-path forest clustering

Nowadays, organizations face the problem of keeping their information protected, available and trustworthy. In this context, machine learning techniques have also been extensively applied to this task. Since manual labeling is very expensive, several works attempt to handle intrusion detection with traditional clustering algorithms. In this paper, we introduce a new pattern recognition technique called Optimum-Path Forest (OPF) clustering to this task. Experiments on three public datasets have showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, since it outperformed some state-of-the-art unsupervised techniques. © 2012 IEEE.

Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems

One objective of the feeder reconfiguration problem in distribution systems is to minimize the power losses for a specific load. For this problem, mathematical modeling is a nonlinear mixed integer problem that is generally hard to solve. This paper proposes an algorithm based on artificial neural network theory. In this context, clustering techniques to determine the best training set for a single neural network with generalization ability are also presented. The proposed methodology was employed for solving two electrical systems and presented good results. Moreover, the methodology can be employed for large-scale systems in real-time environment.

Fault location in underground systems using artificial neural networks and PSCAD/EMTDC

The need for high reliability and environmental concerns are making the underground networks the most appropriate choice of energy distribution. However, like any other system, underground distribution systems are not free of failures. In this context, this work presents an approach to study underground systems using computational tools by integrating the software PSCAD/EMTDC with artificial neural networks to assist fault location in power distribution systems. Targeted benefits include greater accuracy and reduced repair time. The results presented here shows the feasibility of the proposed approach. © 2012 IEEE.

Beta Diversity of Plant-Pollinator Networks and the Spatial Turnover of Pairwise Interactions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Proposta de uma ferramenta de visualização e realidade virtual para o monitoramento de tráfego de redes de computadores

Pós-graduação em Ciência da Computação - IBILCE

An attack signature model to computer security intrusion detection

Internal and external computer network attacks or security threats occur according to standards and follow a set of subsequent steps, allowing to establish profiles or patterns. This well-known behavior is the basis of signature analysis intrusion detection systems. This work presents a new attack signature model to be applied on network-based intrusion detection systems engines. The AISF (ACME! Intrusion Signature Format) model is built upon XML technology and works on intrusion signatures handling and analysis, from storage to manipulation. Using this new model, the process of storing and analyzing information about intrusion signatures for further use by an IDS become a less difficult and standardized process.

The application of distributed virtual machines for enterprise computer management: A two-tier network file system for image provisioning and management

In order to simplify computer management, several system administrators are adopting advanced techniques to manage software configuration of enterprise computer networks, but the tight coupling between hardware and software makes every PC an individual managed entity, lowering the scalability and increasing the costs to manage hundreds or thousands of PCs. Virtualization is an established technology, however its use is been more focused on server consolidation and virtual desktop infrastructure, not for managing distributed computers over a network. This paper discusses the feasibility of the Distributed Virtual Machine Environment, a new approach for enterprise computer management that combines virtualization and distributed system architecture as the basis of the management architecture. © 2008 IEEE.

Network node with wireless and wired interfaces: Nios II processor and uClinux to development of a NCAP embedded (IEEE 1451.1) with two interfaces, wireless (IEEE 1451.5) and wired (IEEE p1451.2)

This paper presents a NCAP embedded on DE2 kit with Nios II processor and uClinux to development of a network gateway with two interfaces, wireless (ZigBee) and wired (RS232) based on IEEE 1451. Both the communications, wireless and wired, were developed to be point-to-point and working with the same protocols, based on IEEE 1451.0-2007. The tests were made using a microcomputer, which through of browser was possible access the web page stored in the DE2 kit and send commands of control and monitoring to both TIMs (WTIM and STIM). The system describes a different form of development of the NCAP node to be applied in different environments with wired or wireless in the same node. © 2011 IEEE.

A Management Tool for the Replication of Operating Systems in Wireless Communication Networks

To simplify computer management, various administration systems based on wired connections adopt advanced techniques to manage software configuration. Nevertheless, the strong relation between hardware and software makes for an individualism of that management, besides penalizing computational mobility and ubiquity. All these issues lead to degradation of scalability, flexibility and the facility to install and maintain distributed applications. This article presents an environment for centralized wireless communication network management, named WSE-OS (Wireless Sharing Environment - Operating Systems): a model based on Virtual Desktop Infrastructure (VDI) which associates virtualization techniques and safe remote access systems to create a distributed architecture as a base for a managing system. WSE-OS is capable of accomplishing the replication of operating system images using wireless communication network, besides offering abstraction of hardware to its clients, making the management more flexible and independent of wired connections. Results obtained from this work indicate that WSE-OS allows disseminating, through a single software configuration, the execution of data related to operating system images in client computers. WSE-OS can also be used as a management tool for operating systems in a wireless network.

Feedforward neural networks based on PPS-wavelet activation functions

Function approximation is a very important task in environments where computation has to be based on extracting information from data samples in real world processes. Neural networks and wavenets have been recently seen as attractive tools for developing efficient solutions for many real world problems in function approximation. In this paper, it is shown how feedforward neural networks can be built using a different type of activation function referred to as the PPS-wavelet. An algorithm is presented to generate a family of PPS-wavelets that can be used to efficiently construct feedforward networks for function approximation.

Open and standardized tools for smart transducer networking

IEEE 1451 Standard is intended to address the smart transducer interfacing problematic in network environments. Usually, proprietary hardware and software is a very efficient solution to in planent the IEEE 1451 normative, although can be expensive and inflexible. In contrast, the use of open and standardized tools for implementing the IEEE 1451 normative is proposed in this paper. Tools such as Java and Phyton programming languages, Linux, programmable logic technology, Personal Computer resources and Ethernet architecture were integrated in order to constructa network node based on the IEEE 1451 standards. The node can be applied in systems based on the client-server communication model The evaluation of the employed tools and expermental results are presented. © 2005 IEEE.

An approach based on neural networks for identification of fault sections in radial distribution systems

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.